Abstract

We propose an extended hazard regression model which allows the spread parameter to be dependent on covariates. This allows a broad class of models which includes the most common hazard models, such as the proportional hazards model, the accelerated failure time model and a proportional hazards/accelerated failure time hybrid model with constant spread parameter. Simulations based on sub-classes of this model suggest that maximum likelihood performs well even when only small or moderate-size data sets are available and the censoring pattern is heavy. The methodology provides a broad framework for analysis of reliability and survival data. Two numerical examples illustrate the results.

References

A. Ciampi and J. Etezadi-Amoli, “A general model for testing the proportional hazards and the accelerated failure time hypothesis in the analysis of censored survival data with covariates,” Communications in Statistics A vol. 14, pp. 651–667, 1985.Google Scholar